Instructions to use Ad-adv/nuextract-tiny-cv-extraction with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Ad-adv/nuextract-tiny-cv-extraction with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("Ad-adv/nuextract-tiny-cv-extraction", dtype="auto") - Notebooks
- Google Colab
- Kaggle
| { | |
| "add_prefix_space": false, | |
| "backend": "tokenizers", | |
| "bos_token": null, | |
| "clean_up_tokenization_spaces": false, | |
| "eos_token": "<|end-output|>", | |
| "errors": "replace", | |
| "extra_special_tokens": [ | |
| "<|im_start|>", | |
| "<|im_end|>" | |
| ], | |
| "is_local": false, | |
| "local_files_only": false, | |
| "max_length": 2048, | |
| "model_max_length": 32768, | |
| "pad_token": "<|endoftext|>", | |
| "split_special_tokens": false, | |
| "stride": 0, | |
| "tokenizer_class": "Qwen2Tokenizer", | |
| "truncation_side": "right", | |
| "truncation_strategy": "longest_first", | |
| "unk_token": null | |
| } | |